Modern electronic devices such as computers, tablets, mobile phones, wearable devices, gaming consoles, televisions, and the like have become a common part of modern life. Many of these devices provide for various digital video capabilities. However, processing digital videos within these applications can be a resource intensive task as the video data can quickly become large. For example, in real-time video communications users often prefer higher resolutions and frame rates which can quickly tax computing resources (e.g., processors, network communication components, etc.). In an effort to mitigate this problem, various video coding formats can be employed to compress video data for storage and/or transmission. Examples of common video coding formats include, but are not limited to, H.265 which is also known as high efficiency video coding (HEVC), H.264 which is also known as advanced video coding (AVC), various moving picture experts group (MPEG) coding formats, and the like.
One of the tradeoffs with these various video coding formats is between compression rate and quality. To help compress the data further, while still being able to provide higher quality videos, many video coding techniques may employ various partitioning and prediction-based methods that take advantage of statistical redundancy within the digital video. However, the demands from users of modern electronic devices continue to increase. As such, additional improvements to current encoding techniques are needed.
Overall, the examples herein of some prior or related systems and their associated limitations are intended to be illustrative and not exclusive. Upon reading the following, other limitations of existing or prior systems will become apparent to those of skill in the art.